Reading in the data
| TYPE | YEAR | MONTH | DAY | HOUR | MINUTE | HUNDRED_BLOCK | NEIGHBOURHOOD | X | Y |
|---|---|---|---|---|---|---|---|---|---|
| Break and Enter Residential/Other | 2003 | 08 | 09 | 00 | 40 | 15XX MARINER WALK | Fairview | 489839.1 | 5457534 |
| Theft of Vehicle | 2003 | 02 | 05 | 22 | 00 | 47XX JOYCE ST | Renfrew-Collingwood | 497984.1 | 5454417 |
| Theft of Vehicle | 2003 | 12 | 22 | 08 | 47 | 47XX KILLARNEY ST | Renfrew-Collingwood | 497037.3 | 5454333 |
| Theft of Vehicle | 2003 | 03 | 24 | 22 | 00 | 47XX LANARK ST | Kensington-Cedar Cottage | 494557.3 | 5454469 |
| Other Theft | 2003 | 12 | 24 | 12 | 15 | 2X W HASTINGS ST | Central Business District | 492353.4 | 5458773 |
| Theft of Vehicle | 2003 | 11 | 17 | 22 | 30 | 47XX LITTLE ST | Kensington-Cedar Cottage | 495337.7 | 5454436 |
How many of each type of crime do we have in our dataset?
| TYPE | counts |
|---|---|
| Theft from Vehicle | 193009 |
| Mischief | 78418 |
| Break and Enter Residential/Other | 64213 |
| Other Theft | 59376 |
| Offence Against a Person | 58578 |
| Theft of Vehicle | 40236 |
| Break and Enter Commercial | 36722 |
| Theft of Bicycle | 28970 |
| Vehicle Collision or Pedestrian Struck (with Injury) | 24015 |
| Vehicle Collision or Pedestrian Struck (with Fatality) | 276 |
| Homicide | 240 |
Counts of total crime by area
Crime counts over time by type of crime
Total crime counts over time by neighbourhood
Car thefts in Vancouver
Counts of car theft reported at each hour of the day
How many neighborhoods do we have in the dataset and how many thefts from cars happened in each?
# A tibble: 25 x 1
NEIGHBOURHOOD
<chr>
1 Riley Park
2 Grandview-Woodland
3 Sunset
4 Mount Pleasant
5 Kensington-Cedar Cottage
6 Central Business District
7 Hastings-Sunrise
8 Kitsilano
9 Strathcona
10 Renfrew-Collingwood
# … with 15 more rows
# A tibble: 24 x 2
NEIGHBOURHOOD count
<chr> <int>
1 Arbutus Ridge 2021
2 Central Business District 54892
3 Dunbar-Southlands 3182
4 Fairview 12884
5 Grandview-Woodland 8300
6 Hastings-Sunrise 6459
7 Kensington-Cedar Cottage 8203
8 Kerrisdale 3044
9 Killarney 4343
10 Kitsilano 9923
# … with 14 more rows
Days of the week
Looking at data between 2003 and 2017 and looking at difference in the days of the week
Seasons
Looking at data between 2003 and 2017 (omitting 2018 because it is incomplete), do we see any variation between summer and winter months. Looking at the plot above it does not appear as though there is any significant difference.
# A tibble: 4 x 5
is_summer is_winter is_fall is_spring n
<lgl> <lgl> <lgl> <lgl> <int>
1 FALSE FALSE FALSE TRUE 43928
2 FALSE FALSE TRUE FALSE 46486
3 FALSE TRUE FALSE FALSE 42512
4 TRUE FALSE FALSE FALSE 44943Incredible. The number of car thefts is nearly the same across all the seasons. The lowest being in winter at 43000 and the highest being Fall at 47000. Over 14 years, that difference is nearly negligible.
Mapping theft from cars for 2004 in Vancouver using Leaflet
NEIGHBOURHOOD X Y
Length:17835 Min. :-123.2 Min. :49.20
Class :character 1st Qu.:-123.1 1st Qu.:49.25
Mode :character Median :-123.1 Median :49.27
Mean :-123.1 Mean :49.26
3rd Qu.:-123.1 3rd Qu.:49.28
Max. :-123.0 Max. :49.31 Mapping theft from cars in Vancouver using ggplot2
OGR data source with driver: KML
Source: "/Users/mohamadmakkaoui/Desktop/Code/van_car_theft_vis/cov_localareas.kml", layer: "local_areas_region"
with 22 features
It has 2 fields
long lat order hole piece id group
1 -123.1641 49.25748 1 FALSE 1 0 0.1
2 -123.1639 49.25746 2 FALSE 1 0 0.1
3 -123.1636 49.25745 3 FALSE 1 0 0.1
4 -123.1626 49.25743 4 FALSE 1 0 0.1
5 -123.1603 49.25740 5 FALSE 1 0 0.1
6 -123.1579 49.25736 6 FALSE 1 0 0.1
Making a choropleth map of Vancouver
Creating our dataset with counts per neighborhood
# A tibble: 6 x 2
NEIGHBOURHOOD n
<chr> <int>
1 Arbutus Ridge 207
2 Central Business District 4418
3 Dunbar-Southlands 419
4 Fairview 1295
5 Grandview-Woodland 794
6 Hastings-Sunrise 602It appears as thought there is some descrepancy between the polygon dataset and the crime dataset when it comes to neighborhood names. Luckily, most of them are correct and will be joinable. The ones that aren’t will be merged using the aggregate function.